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CORR
2012
Springer
170views Education» more  CORR 2012»
13 years 5 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
EMMCVPR
2007
Springer
15 years 3 months ago
Bayesian Order-Adaptive Clustering for Video Segmentation
Video segmentation requires the partitioning of a series of images into groups that are both spatially coherent and smooth along the time axis. We formulate segmentation as a Bayes...
Peter Orbanz, Samuel Braendle, Joachim M. Buhmann
ICIP
2008
IEEE
15 years 11 months ago
Efficient BP stereo with automatic paramemeter estimation
In this paper, we propose a series of techniques to enhance the computational performance of existing Belief Propagation (BP) based stereo matching that relies on automatic estima...
Shafik Huq, Andreas Koschan, Besma R. Abidi, Mongi...
SAT
2009
Springer
91views Hardware» more  SAT 2009»
15 years 4 months ago
VARSAT: Integrating Novel Probabilistic Inference Techniques with DPLL Search
Probabilistic inference techniques can be used to estimate variable bias, or the proportion of solutions to a given SAT problem that fix a variable positively or negatively. Metho...
Eric I. Hsu, Sheila A. McIlraith
ICCSA
2003
Springer
15 years 2 months ago
A Probabilistic Model for Predicting Software Development Effort
—Recently, Bayesian probabilistic models have been used for predicting software development effort. One of the reasons for the interest in the use of Bayesian probabilistic model...
Parag C. Pendharkar, Girish H. Subramanian, James ...